actually did it in app

app.py

@@ -4,14 +4,11 @@ import pandas as pd
 from typing import Tuple, Dict
 from youtube_transcript_api import YouTubeTranscriptApi
 import re
-import json
-from pathlib import Path
 
-# Initialize Anthropic client and settings
+# Initialize Anthropic client
 client = anthropic.Anthropic()
-PROMPTS_FILE = Path("prompts.json")
 
-# Default prompts
+# Default prompts that we can experiment with
 DEFAULT_PROMPTS = {
     "clips": """You are a social media expert for the Dwarkesh Podcast. Generate 10 viral-worthy clips from the transcript.
 Format as:
@@ -48,23 +45,8 @@ Previous examples:
 {titles_and_thumbnails_examples}""",
 }
 
-
-def load_prompts() -> Dict[str, str]:
-    """Load prompts from file or return defaults."""
-    if PROMPTS_FILE.exists():
-        with open(PROMPTS_FILE, "r") as f:
-            return json.load(f)
-    return DEFAULT_PROMPTS
-
-
-def save_prompts(prompts: Dict[str, str]) -> str:
-    """Save prompts to file."""
-    try:
-        with open(PROMPTS_FILE, "w") as f:
-            json.dump(prompts, f, indent=2)
-        return f"Prompts saved to: {PROMPTS_FILE.absolute()}"
-    except Exception as e:
-        return f"Error saving prompts: {str(e)}"
+# Current prompts used in the session
+current_prompts = DEFAULT_PROMPTS.copy()
 
 
 def load_examples(filename: str, columns: list) -> str:
@@ -101,12 +83,11 @@ def generate_content(
         ),
     }
 
-    prompts = load_prompts()
     message = client.messages.create(
         model="claude-3-5-sonnet-20241022",
         max_tokens=max_tokens,
         temperature=temp,
-        system=prompts[prompt_key].format(
+        system=current_prompts[prompt_key].format(
             **{f"{prompt_key}_examples": examples[prompt_key]}
         ),
         messages=[
@@ -161,6 +142,20 @@ def process_transcript(input_text: str) -> Tuple[str, str, str, str]:
         return (error_msg,) * 4
 
 
+def update_prompts(*values) -> str:
+    """Update the current session's prompts."""
+    global current_prompts
+    current_prompts = {
+        "clips": values[0],
+        "description": values[1],
+        "timestamps": values[2],
+        "titles_and_thumbnails": values[3],
+    }
+    return (
+        "Prompts updated for this session! Changes will reset when you reload the page."
+    )
+
+
 def create_interface():
     """Create the Gradio interface."""
     with gr.Blocks(title="Podcast Transcript Analyzer") as app:
@@ -182,56 +177,50 @@ def create_interface():
                 fn=process_transcript, inputs=[input_text], outputs=outputs
             )
 
-        with gr.Tab("Configure Prompts"):
-            gr.Markdown("# Edit Prompts")
-            gr.Markdown(f"Prompts are saved to: `{PROMPTS_FILE.absolute()}`")
+        with gr.Tab("Experiment with Prompts"):
+            gr.Markdown("# Experiment with Prompts")
+            gr.Markdown(
+                """
+            Here you can experiment with different prompts during your session. 
+            Changes will remain active until you reload the page.
+            
+            Tip: Copy your preferred prompts somewhere safe if you want to reuse them later!
+            """
+            )
 
-            prompts = load_prompts()
             prompt_inputs = [
                 gr.Textbox(
-                    label="Clips Prompt",
-                    lines=10,
-                    value=prompts["clips"],
-                    interactive=True,
+                    label="Clips Prompt", lines=10, value=DEFAULT_PROMPTS["clips"]
                 ),
                 gr.Textbox(
                     label="Description Prompt",
                     lines=10,
-                    value=prompts["description"],
-                    interactive=True,
+                    value=DEFAULT_PROMPTS["description"],
                 ),
                 gr.Textbox(
                     label="Timestamps Prompt",
                     lines=10,
-                    value=prompts["timestamps"],
-                    interactive=True,
+                    value=DEFAULT_PROMPTS["timestamps"],
                 ),
                 gr.Textbox(
                     label="Titles & Thumbnails Prompt",
                     lines=10,
-                    value=prompts["titles_and_thumbnails"],
-                    interactive=True,
+                    value=DEFAULT_PROMPTS["titles_and_thumbnails"],
                 ),
             ]
             status = gr.Textbox(label="Status", interactive=False)
 
-            def save_prompts_callback(*values):
-                new_prompts = {
-                    "clips": values[0],
-                    "description": values[1],
-                    "timestamps": values[2],
-                    "titles_and_thumbnails": values[3],
-                }
-                return save_prompts(new_prompts)
-
+            # Update prompts when they change
             for prompt in prompt_inputs:
-                prompt.change(
-                    fn=save_prompts_callback, inputs=prompt_inputs, outputs=[status]
-                )
+                prompt.change(fn=update_prompts, inputs=prompt_inputs, outputs=[status])
 
+            # Reset button
             reset_btn = gr.Button("Reset to Default Prompts")
             reset_btn.click(
-                fn=lambda: (save_prompts(DEFAULT_PROMPTS), *DEFAULT_PROMPTS.values()),
+                fn=lambda: (
+                    update_prompts(*DEFAULT_PROMPTS.values()),
+                    *DEFAULT_PROMPTS.values(),
+                ),
                 outputs=[status] + prompt_inputs,
             )
 

producer.py

@@ -1,231 +0,0 @@
-import gradio as gr
-import anthropic
-import pandas as pd
-from typing import Tuple, Dict
-from youtube_transcript_api import YouTubeTranscriptApi
-import re
-
-# Initialize Anthropic client
-client = anthropic.Anthropic()
-
-# Default prompts that we can experiment with
-DEFAULT_PROMPTS = {
-    "clips": """You are a social media expert for the Dwarkesh Podcast. Generate 10 viral-worthy clips from the transcript.
-Format as:
-Tweet 1
-Tweet Text: [text]
-Clip Transcript: [45-120 seconds of transcript]
-
-Previous examples:
-{clips_examples}""",
-    "description": """Create an engaging episode description tweet (280 chars max) that:
-1. Highlights compelling aspects
-2. Includes topic areas and handles
-3. Ends with "Links below" or "Enjoy!"
-
-Previous examples:
-{description_examples}""",
-    "timestamps": """Generate timestamps (HH:MM:SS) every 3-8 minutes covering key transitions and moments.
-Use 2-6 word descriptions.
-Start at 00:00:00.
-
-Previous examples:
-{timestamps_examples}""",
-    "titles_and_thumbnails": """Create 3-5 compelling title-thumbnail combinations that tell a story.
-
-Title Format: "Guest Name – Key Story or Core Insight"
-Thumbnail: 2-4 ALL CAPS words that create intrigue with the title
-
-Example: "David Reich – How One Small Tribe Conquered the World 70,000 Years Ago"
-Thumbnail: "LAST HUMANS STANDING"
-
-The combination should create intellectual curiosity without clickbait.
-
-Previous examples:
-{titles_and_thumbnails_examples}""",
-}
-
-# Current prompts used in the session
-current_prompts = DEFAULT_PROMPTS.copy()
-
-
-def load_examples(filename: str, columns: list) -> str:
-    """Load examples from CSV file."""
-    try:
-        df = pd.read_csv(filename)
-        if len(columns) == 1:
-            examples = df[columns[0]].dropna().tolist()
-            return "\n\n".join(examples)
-
-        examples = []
-        for _, row in df.iterrows():
-            if all(pd.notna(row[col]) for col in columns):
-                example = "\n".join(f"{col}: {row[col]}" for col in columns)
-                examples.append(example)
-        return "\n\n".join(examples)
-    except Exception as e:
-        print(f"Error loading {filename}: {str(e)}")
-        return ""
-
-
-def generate_content(
-    prompt_key: str, transcript: str, max_tokens: int = 1000, temp: float = 0.6
-) -> str:
-    """Generate content using Claude."""
-    examples = {
-        "clips": load_examples(
-            "Viral Twitter Clips.csv", ["Tweet Text", "Clip Transcript"]
-        ),
-        "description": load_examples("Viral Episode Descriptions.csv", ["Tweet Text"]),
-        "timestamps": load_examples("Timestamps.csv", ["Timestamps"]),
-        "titles_and_thumbnails": load_examples(
-            "Titles & Thumbnails.csv", ["Titles", "Thumbnail"]
-        ),
-    }
-
-    message = client.messages.create(
-        model="claude-3-5-sonnet-20241022",
-        max_tokens=max_tokens,
-        temperature=temp,
-        system=current_prompts[prompt_key].format(
-            **{f"{prompt_key}_examples": examples[prompt_key]}
-        ),
-        messages=[
-            {
-                "role": "user",
-                "content": [
-                    {
-                        "type": "text",
-                        "text": f"Process this transcript:\n\n{transcript}",
-                    }
-                ],
-            }
-        ],
-    )
-    return message.content[0].text
-
-
-def get_youtube_transcript(url: str) -> str:
-    """Get transcript from YouTube URL."""
-    try:
-        video_id = re.search(
-            r"(?:youtube\.com\/watch\?v=|youtu\.be\/|youtube\.com\/embed\/|youtube\.com\/v\/)([A-Za-z0-9_-]+)",
-            url,
-        ).group(1)
-        transcript = YouTubeTranscriptApi.list_transcripts(video_id).find_transcript(
-            ["en"]
-        )
-        return " ".join(entry["text"] for entry in transcript.fetch())
-    except Exception as e:
-        raise Exception(f"Error fetching YouTube transcript: {str(e)}")
-
-
-def process_transcript(input_text: str) -> Tuple[str, str, str, str]:
-    """Process input and generate all content."""
-    try:
-        # Get transcript from URL or use direct input
-        transcript = (
-            get_youtube_transcript(input_text)
-            if any(x in input_text for x in ["youtube.com", "youtu.be"])
-            else input_text
-        )
-
-        # Generate all content types
-        return (
-            generate_content("clips", transcript, max_tokens=8192),
-            generate_content("description", transcript),
-            generate_content("timestamps", transcript, temp=0.4),
-            generate_content("titles_and_thumbnails", transcript, temp=0.7),
-        )
-    except Exception as e:
-        error_msg = f"Error processing input: {str(e)}"
-        return (error_msg,) * 4
-
-
-def update_prompts(*values) -> str:
-    """Update the current session's prompts."""
-    global current_prompts
-    current_prompts = {
-        "clips": values[0],
-        "description": values[1],
-        "timestamps": values[2],
-        "titles_and_thumbnails": values[3],
-    }
-    return (
-        "Prompts updated for this session! Changes will reset when you reload the page."
-    )
-
-
-def create_interface():
-    """Create the Gradio interface."""
-    with gr.Blocks(title="Podcast Transcript Analyzer") as app:
-        with gr.Tab("Generate Content"):
-            gr.Markdown("# Podcast Content Generator")
-            input_text = gr.Textbox(
-                label="Input", placeholder="YouTube URL or transcript...", lines=10
-            )
-            submit_btn = gr.Button("Generate Content")
-            outputs = [
-                gr.Textbox(label="Twitter Clips", lines=10, interactive=False),
-                gr.Textbox(label="Twitter Description", lines=3, interactive=False),
-                gr.Textbox(label="Timestamps", lines=10, interactive=False),
-                gr.Textbox(
-                    label="Title & Thumbnail Suggestions", lines=10, interactive=False
-                ),
-            ]
-            submit_btn.click(
-                fn=process_transcript, inputs=[input_text], outputs=outputs
-            )
-
-        with gr.Tab("Experiment with Prompts"):
-            gr.Markdown("# Experiment with Prompts")
-            gr.Markdown(
-                """
-            Here you can experiment with different prompts during your session. 
-            Changes will remain active until you reload the page.
-            
-            Tip: Copy your preferred prompts somewhere safe if you want to reuse them later!
-            """
-            )
-
-            prompt_inputs = [
-                gr.Textbox(
-                    label="Clips Prompt", lines=10, value=DEFAULT_PROMPTS["clips"]
-                ),
-                gr.Textbox(
-                    label="Description Prompt",
-                    lines=10,
-                    value=DEFAULT_PROMPTS["description"],
-                ),
-                gr.Textbox(
-                    label="Timestamps Prompt",
-                    lines=10,
-                    value=DEFAULT_PROMPTS["timestamps"],
-                ),
-                gr.Textbox(
-                    label="Titles & Thumbnails Prompt",
-                    lines=10,
-                    value=DEFAULT_PROMPTS["titles_and_thumbnails"],
-                ),
-            ]
-            status = gr.Textbox(label="Status", interactive=False)
-
-            # Update prompts when they change
-            for prompt in prompt_inputs:
-                prompt.change(fn=update_prompts, inputs=prompt_inputs, outputs=[status])
-
-            # Reset button
-            reset_btn = gr.Button("Reset to Default Prompts")
-            reset_btn.click(
-                fn=lambda: (
-                    update_prompts(*DEFAULT_PROMPTS.values()),
-                    *DEFAULT_PROMPTS.values(),
-                ),
-                outputs=[status] + prompt_inputs,
-            )
-
-    return app
-
-
-if __name__ == "__main__":
-    create_interface().launch()